High sensing margin and parallelism 6T-2MTJ SOT-MRAM based TCAM for energy-Efficient Similarity Priority calculation in MANNs

With the development of AI applications, there is a demand for high parallel similarity priority calculation, like in MANNs. TCAM, as a type of memory for high parallel searching work, is suitable to perform the task. However, the CMOS based TCAMs suffer from area overhead, static power consumption and data-loss while power failure. The SOT-MRAM presents a promising alternative for TCAM design due to its nonvolatility, low area overhead and no static power consumption. But, its low on/off ratio results in low sensing margin which limits its processing speed. To address the challenges, we propose a novel TCAM structure with high sensing margin, parallelism and low energy consumption. This work proposes the followings: (1) A novel 6T-2MTJ sot-mram based TCAM structure is proposed. Simulations show it has a 2-3x improvement in sensing margin over other MRAM based ones, 1.37x improvement in searching energy (fJ/bit) over other nonvolatile technologies based ones, and 23% area reduction over other CMOS based ones. (2) A segmented power supply scheme is presented to meet the parallelism need of MANNs which improves the parallelism by 4-8x compared to no segmented one.